• Title, Summary, Keyword: obstacle avoidance

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An Obstacle Avoidance Trajectory Planning for a Quadruped Walking Robot Using Vision and PSD sensor

  • Kong, Jung-Shik;Lee, Bo-Hee;Kim, Jin-Geol
    • 제어로봇시스템학회:학술대회논문집
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    • pp.105.1-105
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    • 2002
  • $\textbullet$ This paper deals with obstacle avoidance of a quadruped robot with a vision system and a PSD sensor. $\textbullet$ The vision system needs for obstacle recognition toward robot. $\textbullet$ Ths PSD sensor is also important element for obstacle recognition. $\textbullet$ We propose algorithm that recognizes obstacles with one vision and PSD sensor. $\textbullet$ We also propose obstacle avoidance algorithm with map from obstacle recognition algorithm. $\textbullet$ Using these algorithm, Quadruped robot can generate gait trajectory. $\textbullet$ Therefore, robot can avoid obstacls, and can move to target point.

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Obstacle Avoidance by the Subgoal Generation Using the Infrared Sensors (적외선 센서를 이용한 서브 골 생성에 의한 장애물 회피)

  • Nakazawa, Kazuki;Yang, Dong-Hoon;Kim, Il-Teak;Hong, Suk-Kyo
    • Proceedings of the KIEE Conference
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    • pp.490-492
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    • 2004
  • This paper presents an obstacle avoidance of a mobile robot by the subgoal generation using infrared sensors. When an obstacle appears on the path which the robot is moving forward the robot has to get information, such as distance between the robot and the obstacle and the shape of the obstacle for avoidance behavior. Our collision avoidance algorithm needs the only distance between the robot and the obstacles. The distances are used for subgoal generation. Simulation results show that a robot can go to the goal, carrying out subgoal generation and avoiding obstacles.

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Obstacle Avoidance System Using a Single Camera and LMNN Fuzzy Controller (단일 영상과 LM 신경망 퍼지제어기를 적용한 장애물 회피 시스템)

  • Yoo, Sung-Goo;Chong, Kil-To
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.2
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    • pp.192-197
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    • 2009
  • In this paper, we proposed the obstacle avoidance system using a single camera image and LM(Levenberg-Marquart) neural network fuzzy controller. According to a robot technology adapt to various fields of industry and public, the robot has to move using self-navigation and obstacle avoidance algorithms. When the robot moves to target point, obstacle avoidance is must-have technology. So in this paper, we present the algorithm that avoidance method based on fuzzy controller by sensing data and image information from a camera and using the LM neural network to minimize the moving error. And then to verify the system performance of the simulation test.

Autonomous Navigation of an Underwater Robot in the Presence of Multiple Moving Obstacles

  • Kwon, Kyoung-Youb;Joh, Joong-Seon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.2
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    • pp.124-130
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    • 2005
  • Obstacle avoidance of underwater robots based on a modified virtual force field algorithm is proposed in this paper. The VFF(Virtual Force Field) algorithm, which is widely used in the field of mobile robots, is modified for application to the obstacle avoidance of underwater robots. This Modified Virtual Force Field(MVFF) algorithm using the fuzzy lgoc can be used in moving obstacles avoidance. A fuzzy algorithm is devised to handle various situations which can be faced during autonomous navigation of underwater robots. The proposed obstacle avoidance algorithm has ability to handle multiple moving obstacles. Results of simulation show that the proposed algorithm can be efficiently applied to obstacle avoidance of the underwater robots.

Local Obstacle Avoidance of Nonholonomic Wheeled Mobile Robots in Trajectory Tracking

  • Lee, Young-Ho;Park, Jong-Hyeon
    • 제어로봇시스템학회:학술대회논문집
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    • pp.1172-1177
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    • 2003
  • In this paper, we propose an obstacle avoidance technique in trajectory tracking of nonholonomic wheeled mobile robots. Input-output linearized backstepping controller is used in trajectory tracking, and repulsive type control input for obstacle avoidance is added to it. The added input is generated by fuzzy logic. And we do not add the two inputs directly but combine them via fuzzy logic, which determines the ratings of each input. Some simulations are performed to show that with the proposed algorithm, the mobile robot can track its reference trajectory even if there are multiple obstacles on the trajectory of robot.

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Obstacle Avoidance of Autonomous Mobile Agent using Circular Navigation Method (곡률 주행 기법을 이용한 무인 이동 개체의 장애물 회피 알고리즘)

  • Lee, Jin-Seob;Chwa, Dong-Kyoung;Hong, Suk-Kyo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.4
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    • pp.824-831
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    • 2009
  • This paper proposes an obstacle avoidance algorithm for an autonomous mobile robot. The proposed method based on the circular navigation with probability distribution finds local-paths to avoid collisions. Futhermore, it makes mobile robots to achieve obstacle avoidance and optimal path planning due to the accurate decision of the final goal. Simulation results are included to show the feasibility of the proposed method.

Moving obstacle avoidance of a robot using avoidability measure (충돌 회피 가능도를 이용한 로봇의 이동 장애물 회피)

  • Ko, Nak-Yong;Lee, Beom-Hee
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.2
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    • pp.169-178
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    • 1997
  • This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept, avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of three state variables: the distance from the obstacle to the robot, outward speed of the obstacle relative to the robot, and outward speed of the robot relative to the obstacle. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid a moving obstacle in real time. Since the algorithm considers the mobility of the obstacle and robot as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

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Practical Study about Obstacle Detecting and Collision Avoidance Algorithm for Unmanned Vehicle

  • Park, Eun-Young;Lee, Woon-Sung;Kim, Jung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • pp.487-490
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    • 2003
  • In this research, we will devise an obstacle avoidance algorithm for a previously unmanned vehicle. Whole systems consist mainly of the vehicle system and the control system. The two systems are separated; this system can communicate with the vehicle system and the control system through wireless RF (Radio Frequency) modules. These modules use wireless communication. And the vehicle system is operated on PIC Micro Controller. Obstacle avoidance method for unmanned vehicle is based on the Virtual Force Field (VFF) method. An obstacle exerts repulsive forces and the lane center point applies an attractive force to the unmanned vehicle. A resultant force vector, comprising of the sum of a target directed attractive force and repulsive forces from an obstacle, is calculated for a given unmanned vehicle position. With resultant force acting on the unmanned vehicle, the vehicle's new driving direction is calculated, the vehicle makes steering adjustments, and this algorithm is repeated.

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Obstacle Parameter Modeling for Model Predictive Control of the Unmanned Vehicle (무인자동차의 모델 예측제어를 위한 장애물 파라미터 모델링 기법)

  • Yeu, Jung-Yun;Kim, Woo-Hyun;Im, Jun-Hyuck;Lee, Dal-Ho;Jee, Gyu-In
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.12
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    • pp.1132-1138
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    • 2012
  • The MPC (Model Predictive Control) is one of the techniques that can be used to control an unmanned vehicle. It predicts the future vehicle trajectory using the dynamic characteristic of the vehicle and generate the control value to track the reference path. If some obstacles are detected on the reference paths, the MPC can generate control value to avoid the obstacles imposing the inequality constraints on the MPC cost function. In this paper, we propose an obstacle modeling algorithm for MPC with inequality constraints for obstacle avoidance and a method to set selective constraint on the MPC for stable obstacle avoidance. Simulations with the field test data show successful obstacle avoidance and way point tracking performance.

3D Vision-Based Local Path Planning System of a Humanoid Robot for Obstacle Avoidance

  • Kang, Tae-Koo;Lim, Myo-Taeg;Park, Gwi-Tae;Kim, Dong W.
    • Journal of Electrical Engineering and Technology
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    • v.8 no.4
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    • pp.879-888
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    • 2013
  • This paper addresses the vision based local path planning system for obstacle avoidance. To handle the obstacles which exist beyond the field of view (FOV), we propose a Panoramic Environment Map (PEM) using the MDGHM-SIFT algorithm. Moreover, we propose a Complexity Measure (CM) and Fuzzy logic-based Avoidance Motion Selection (FAMS) system to enable a humanoid robot to automatically decide its own direction and walking motion when avoiding an obstacle. The CM provides automation in deciding the direction of avoidance, whereas the FAMS system chooses the avoidance path and walking motion, based on environment conditions such as the size of the obstacle and the available space around it. The proposed system was applied to a humanoid robot that we designed. The results of the experiment show that the proposed method can be effectively applied to decide the avoidance direction and the walking motion of a humanoid robot.